{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using LAMMPS with iPython and Jupyter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "LAMMPS can be run interactively using iPython easily. This tutorial shows how to set this up."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Installation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Download the latest version of LAMMPS into a folder (we will calls this `$LAMMPS_DIR` from now on)\n",
    "2. Compile LAMMPS as a shared library and enable exceptions and PNG support\n",
    "   ```bash\n",
    "   cd $LAMMPS_DIR/src\n",
    "   make mpi mode=shlib LMP_INC=\"-DLAMMPS_PNG -DLAMMPS_EXCEPTIONS\" JPG_LIB=\"-lpng\"\n",
    "   ```\n",
    "\n",
    "3. Create a python virtualenv\n",
    "   ```bash\n",
    "   virtualenv testing\n",
    "   source testing/bin/activate\n",
    "   ```\n",
    "\n",
    "4. Inside the virtualenv install the lammps package\n",
    "   ```\n",
    "   (testing) cd $LAMMPS_DIR/python\n",
    "   (testing) python install.py\n",
    "   (testing) cd   # move to your working directory\n",
    "   ```\n",
    "\n",
    "5. Install jupyter and ipython in the virtualenv\n",
    "   ```bash\n",
    "   (testing) pip install ipython jupyter\n",
    "   ```\n",
    "\n",
    "6. Run jupyter notebook\n",
    "   ```bash\n",
    "   (testing) jupyter notebook\n",
    "   ```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from lammps import IPyLammps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L = IPyLammps()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "\n",
    "# 3d Lennard-Jones melt\n",
    "\n",
    "L.units(\"lj\")\n",
    "L.atom_style(\"atomic\")\n",
    "L.atom_modify(\"map array\")\n",
    "\n",
    "L.lattice(\"fcc\", 0.8442)\n",
    "L.region(\"box\", \"block\", 0, 4, 0, 4, 0, 4)\n",
    "L.create_box(1, \"box\")\n",
    "L.create_atoms(1, \"box\")\n",
    "L.mass(1, 1.0)\n",
    "\n",
    "L.velocity(\"all\", \"create\", 1.44, 87287, \"loop geom\")\n",
    "\n",
    "L.pair_style(\"lj/cut\", 2.5)\n",
    "L.pair_coeff(1, 1, 1.0, 1.0, 2.5)\n",
    "\n",
    "L.neighbor(0.3, \"bin\")\n",
    "L.neigh_modify(\"delay\", 0, \"every\", 20, \"check no\")\n",
    "\n",
    "L.fix(\"1 all nve\")\n",
    "\n",
    "L.variable(\"fx atom fx\")\n",
    "\n",
    "L.info(\"all\")\n",
    "\n",
    "L.run(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "L.image(zoom=1.0)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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